{"id":225448,"date":"2024-07-25T14:01:34","date_gmt":"2024-07-25T21:01:34","guid":{"rendered":"https:\/\/zpesystems.com\/?p=225448"},"modified":"2024-07-25T14:01:49","modified_gmt":"2024-07-25T21:01:49","slug":"edge-computing-use-cases-in-retail-zs","status":"publish","type":"post","link":"https:\/\/zpesystems.com\/edge-computing-use-cases-in-retail-zs\/","title":{"rendered":"Edge Computing Use Cases in Retail"},"content":{"rendered":"

[et_pb_section fb_built=”1″ admin_label=”section” _builder_version=”4.16″ da_disable_devices=”off|off|off” global_colors_info=”{}” da_is_popup=”off” da_exit_intent=”off” da_has_close=”on” da_alt_close=”off” da_dark_close=”off” da_not_modal=”on” da_is_singular=”off” da_with_loader=”off” da_has_shadow=”on”][et_pb_row _builder_version=”4.17.4″ _module_preset=”default” width=”100%” custom_margin=”0px||||false|false” custom_padding=”0px||||false|false” locked=”off” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.17.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_image src=”https:\/\/zpesystems.com\/wp-content\/uploads\/2024\/07\/Automated-transportation-robots-move-boxes-in-a-warehouse-one-of-many-edge-computing-use-cases-in-retail.jpg” alt=”Automated transportation robots move boxes in a warehouse, one of many edge computing use cases in retail” title_text=”Automated transportation robots move boxes in a warehouse, one of many edge computing use cases in retail” admin_label=”Image” _builder_version=”4.27.0″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_image][et_pb_text _builder_version=”4.27.0″ _module_preset=”default” global_colors_info=”{}”]Retail organizations must constantly adapt to meet changing customer expectations, mitigate external economic forces, and stay ahead of the competition. Technologies like the Internet of Things (IoT), artificial intelligence (AI), and other forms of automation help companies improve the customer experience and deliver products at the pace demanded in the age of one-click shopping and two-day shipping. However, connecting individual retail locations to applications in the cloud or centralized data center increases network latency, security risks, and bandwidth utilization costs.<\/p>\n

Edge computing mitigates many of these challenges by decentralizing cloud and data center resources and distributing them at the network\u2019s \u201cedges,\u201d where most retail operations take place. Running applications and processing data at the edge enables real-time analysis and insights and ensures that systems remain operational even if Internet access is disrupted by an ISP outage or natural disaster. This blog describes five potential edge computing use cases in retail and provides more information about the benefits of edge computing for the retail industry.<\/p>\n

5 Edge computing use cases in retail<\/h2>\n

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1. Security video analysis<\/h3>\n

Security cameras are crucial to loss prevention, but constantly monitoring video surveillance feeds is tedious and difficult for even the most experienced personnel. AI-powered video surveillance systems use machine learning to analyze video feeds and detect suspicious activity with greater vigilance and accuracy. Edge computing enhances AI surveillance by allowing solutions to analyze video feeds in real-time, potentially catching shoplifters in the act and preventing inventory shrinkage.<\/p>\n

2. Localized, real-time insights<\/h3>\n

Retailers have a brief window to meet a customer\u2019s needs before they get frustrated and look elsewhere, especially in a brick-and-mortar store. A retail store can use an edge computing application to learn about customer behavior and purchasing activity in real-time. For example, they can use this information to rotate the products featured on aisle endcaps to meet changing demand, or staff additional personnel in high-traffic departments at certain times of day. Stores can also place QR codes on shelves that customers scan if a product is out of stock, immediately alerting a nearby representative to provide assistance.<\/p>\n

3. Enhanced inventory management<\/h3>\n

Effective inventory management is challenging even for the most experienced retail managers, but ordering too much or too little product can significantly affect sales. Edge computing applications can improve inventory efficiency by making ordering recommendations based on observed purchasing patterns combined with real-time stocking updates as products are purchased or returned. Retailers can use this information to reduce carrying costs for unsold merchandise while preventing out-of-stocks, improving overall profit margins.
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Learn more about edge computing<\/b><\/span><\/p>\n<\/td>\n<\/tr>\n

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